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Deep Learning for Beginners

You're reading from   Deep Learning for Beginners A beginner's guide to getting up and running with deep learning from scratch using Python

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Product type Paperback
Published in Sep 2020
Publisher Packt
ISBN-13 9781838640859
Length 432 pages
Edition 1st Edition
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Authors (2):
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Pablo Rivas Pablo Rivas
Author Profile Icon Pablo Rivas
Pablo Rivas
Dr. Pablo Rivas Dr. Pablo Rivas
Author Profile Icon Dr. Pablo Rivas
Dr. Pablo Rivas
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Getting Up to Speed
2. Introduction to Machine Learning FREE CHAPTER 3. Setup and Introduction to Deep Learning Frameworks 4. Preparing Data 5. Learning from Data 6. Training a Single Neuron 7. Training Multiple Layers of Neurons 8. Section 2: Unsupervised Deep Learning
9. Autoencoders 10. Deep Autoencoders 11. Variational Autoencoders 12. Restricted Boltzmann Machines 13. Section 3: Supervised Deep Learning
14. Deep and Wide Neural Networks 15. Convolutional Neural Networks 16. Recurrent Neural Networks 17. Generative Adversarial Networks 18. Final Remarks on the Future of Deep Learning 19. Other Books You May Enjoy

Diving into the ML ecosystem

From the typical ML application process depicted in Figure 1.1, you can see that ML has a broad range of applications. However, ML algorithms are only a small part of a bigger ecosystem with a lot of moving parts, and yet ML is transforming lives around the world today:

Figure 1.1 - ML ecosystem. ML interacts with the world through several stages of data manipulation and interpretation to achieve an overall system integration

Deployed ML applications usually start with a process of data collection that uses sensors of different types, such as cameras, lasers, spectroscopes, or other types of direct access to data, including local and remote databases, big or small. In the simplest of cases, input can be gathered through a computer keyboard or smartphone screen taps. At this stage, the data collected or sensed is considered to be raw data.

Raw data is usually preprocessed before presenting it to an ML model. Raw data is rarely the actual input to ML algorithms...

You have been reading a chapter from
Deep Learning for Beginners
Published in: Sep 2020
Publisher: Packt
ISBN-13: 9781838640859
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